Slyracoon23/medical-gemma3n-emergency-response

🏥 Medical Emergency Response AI - Gemma 3N (Fine-tuned)

A fine-tuned version of Gemma 3N designed for emergency response scenarios. Powers the Citizen2Responder app with dual-mode capabilities: natural guidance for bystanders and structured tool outputs for EMTs — all with a privacy-first, local deployment focus.

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🧠 Model Summary

• Type: Causal Language Model
• Base Model: unsloth/gemma-3n-E4B-it
• Parameters: 4B
• Adapters: LoRA
• Language: English
• License: Apache 2.0
• Trained with: Unsloth + LoRA
• Author: Citizen2Responder Team
• Model Repo: GitHub
• HF Page: Hugging Face

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✅ Key Features

🗣️ Natural Conversation Mode

• Step-by-step emergency guidance
• No medical jargon
• Real-time questioning & coaching

🔧 Tool Calling Mode

• Generates structured EMT/dispatch reports
• JSON-style outputs for system use

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🚫 Limitations

• Not a substitute for professional medical help
• Not for non-emergency or specialized medical conditions
• Should not replace EMTs in critical care situations

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💻 Usage Example

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Slyracoon23/medical-gemma3n-emergency-response")
tokenizer = AutoTokenizer.from_pretrained("Slyracoon23/medical-gemma3n-emergency-response")

# Natural guidance mode
prompt = "Someone collapsed and is not responding. What should I assess first?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

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📊 Evaluation

• ✅ Recognizes emergency types (>95%)
• ✅ Accurate tool calls (>90%)
• ✅ EMT-approved safety outputs
• ✅ Mobile ready (GGUF quantized)

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🔐 Deployment & Privacy

• Local/mobile deployment (no cloud)
• ~2.5GB size (quantized)
• Compatible with iOS/Android via llama.rn

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📚 Citation

@misc{medical-gemma3n-emergency-response,
  title={Medical Emergency Response AI - Gemma 3N Fine-tuned},
  author={Citizen2Responder Team},
  year={2025},
  url={https://huggingface.co/Slyracoon23/medical-gemma3n-emergency-response},
  note={Fine-tuned for dual-mode emergency response with privacy-first architecture}
}

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⚠️ Disclaimer

This model is for educational and emergency guidance only. Always contact professional medical services in real emergencies.